I’ve noticed a significant shift in recent job descriptions and internal expectations for PMs. The ask is no longer just to be ‘data-informed’ but to be hands-on with data in a way that borders on a data analyst role. We’re talking SQL queries, BI dashboard creation, and even light scripting to parse logs.
This acceleration seems driven by the rise of AI/ML features. To build a truly intelligent product, we need to deeply understand the data models, the training sets, and the statistical outputs. It’s tough to write a good PRD for an AI feature without getting your hands dirty in the data.
But it raises a critical question about our role. Is this a necessary evolution for the modern PM, or are we being pulled too far into the weeds? We are hired to be the voice of the customer and to own the ‘why’ behind the product. When we spend our days debugging queries or wrangling datasets, are we losing the strategic altitude required to see the bigger picture and connect with user needs? Or is this deep data proficiency now the only way to effectively guide technical teams and build truly innovative products?
Where do you and your organization draw the line between being a data-informed PM and a de facto data analyst?